BG value stats by hour

BGvalue_Summary
##    time3 min   mean  max        sd
## 1  00:00 Inf    NaN -Inf       NaN
## 2  01:00  78  78.00   78   0.00000
## 3  02:00 150 150.00  150       NaN
## 4  03:00 Inf    NaN -Inf       NaN
## 5  04:00 105 105.00  105   0.00000
## 6  05:00 Inf    NaN -Inf       NaN
## 7  06:00 304 371.00  511  97.66268
## 8  07:00 234 234.00  234       NaN
## 9  08:00 107 191.00  275  96.99485
## 10 09:00 198 198.00  198   0.00000
## 11 10:00 106 168.50  231  72.16878
## 12 11:00 110 110.00  110       NaN
## 13 12:00  65 120.40  176  51.84882
## 14 13:00  64 148.00  190  72.74613
## 15 14:00 Inf    NaN -Inf       NaN
## 16 15:00 122 122.00  122   0.00000
## 17 16:00 256 256.00  256   0.00000
## 18 17:00  71 130.25  242  76.10683
## 19 18:00  71  71.00   71       NaN
## 20 19:00  79 131.50  187  60.67125
## 21 20:00  44 138.00  232 108.54185
## 22 21:00 161 161.00  161       NaN
## 23 22:00 107 142.50  178  50.20458
## 24 23:00 Inf    NaN -Inf       NaN
## 25 00:00 116 156.50  197  46.76537

BG value stats by day

BGvalue_SummaryDaily
##        Date2 min     mean max        sd
## 1 2019-10-07  71 159.4167 365  83.45435
## 2 2019-10-08  79 154.0625 304  74.52290
## 3 2019-10-09  44 141.3846 242  63.46723
## 4 2019-10-10  44 212.4615 511 124.61181

Sensor value stats by hour

Sensorvalue_Summary
##    time3 min      mean max        sd
## 1  00:00  85 125.08333 183  33.54026
## 2  01:00  67 122.00000 193  36.93064
## 3  02:00  75 154.50000 265  56.09984
## 4  03:00  76 207.47917 320  88.43485
## 5  04:00  59 249.27083 400 114.97673
## 6  05:00  83 272.77083 400 109.70196
## 7  06:00 128 294.12500 400  85.11335
## 8  07:00 120 265.85366 395  81.21563
## 9  08:00  85 165.80435 280  54.60387
## 10 09:00 108 170.56250 214  33.70075
## 11 10:00  60 165.64583 211  53.06619
## 12 11:00  62 121.08108 197  35.23680
## 13 12:00  40  98.08333 175  50.46548
## 14 13:00  40 164.84783 284  59.46763
## 15 14:00 107 231.56250 373  77.98606
## 16 15:00  87 220.97917 362  89.78805
## 17 16:00 112 197.52083 313  52.59196
## 18 17:00  53 134.91667 245  57.98893
## 19 18:00  40 120.79167 225  57.14482
## 20 19:00  51 120.34091 197  48.90662
## 21 20:00  40 134.76190 224  58.92194
## 22 21:00  69 118.47917 201  34.68336
## 23 22:00  87 136.08333 225  34.72006
## 24 23:00  86 154.66667 199  34.26203
## 25 00:00  88 134.62500 189  39.91166

BG high (>150) count

BGHigh_Count
##    time3 BG.Reading..mg.dL.
## 1  06:00                  4
## 2  07:00                  1
## 3  08:00                  2
## 4  09:00                  2
## 5  10:00                  2
## 6  12:00                  1
## 7  13:00                  2
## 8  16:00                  3
## 9  17:00                  1
## 10 19:00                  2
## 11 20:00                  2
## 12 21:00                  1
## 13 22:00                  1
## 14 00:00                  2

BG very high (>240) count

BGveryHigh_Count
##   time3 BG.Reading..mg.dL.
## 1 06:00                  4
## 2 08:00                  2
## 3 16:00                  3
## 4 17:00                  1

BG low (<80) count

BGLow_Count
##   time3 BG.Reading..mg.dL.
## 1 01:00                  2
## 2 12:00                  2
## 3 13:00                  1
## 4 17:00                  1
## 5 18:00                  1
## 6 19:00                  2
## 7 20:00                  2

BG good value count (>80 and <150)

BGgood_Count
##    time3 BG.Reading..mg.dL.
## 1  02:00                  1
## 2  04:00                  2
## 3  08:00                  2
## 4  10:00                  2
## 5  11:00                  1
## 6  12:00                  2
## 7  15:00                  2
## 8  17:00                  2
## 9  22:00                  1
## 10 00:00                  2

Temp Basal = 0 count

tempBasal_count
## NULL

Suspend basal on low count

suspendBasal_Count
##    time3 Alarm
## 1  00:00     1
## 2  01:00     2
## 3  02:00     1
## 4  04:00     4
## 5  07:00     1
## 6  10:00     1
## 7  11:00     2
## 8  12:00     4
## 9  13:00     1
## 10 15:00     2
## 11 17:00     4
## 12 18:00     2
## 13 19:00     3
## 14 20:00     3
## 15 21:00     2
## 16 23:00     1
## 17 00:00     2

BG value by time and date with mean values

BGvalue_timeDaytable
##     time 2019-10-07 2019-10-08 2019-10-09 2019-10-10     mean
## 1  00:00        NaN   116.0000        197        NaN 156.5000
## 2  01:00     78.000        NaN        NaN        NaN  78.0000
## 3  02:00        NaN        NaN        150        NaN 150.0000
## 4  03:00        NaN        NaN        NaN        NaN      NaN
## 5  04:00        NaN        NaN        105        NaN 105.0000
## 6  05:00        NaN        NaN        NaN        NaN      NaN
## 7  06:00    365.000   304.0000        NaN    511.000 393.3333
## 8  07:00        NaN        NaN        234        NaN 234.0000
## 9  08:00        NaN   107.0000        NaN    275.000 191.0000
## 10 09:00    198.000        NaN        NaN        NaN 198.0000
## 11 10:00        NaN        NaN        106    231.000 168.5000
## 12 11:00        NaN        NaN        NaN    110.000 110.0000
## 13 12:00    148.000   176.0000        NaN     65.000 129.6667
## 14 13:00    190.000        NaN         64        NaN 127.0000
## 15 14:00        NaN        NaN        NaN        NaN      NaN
## 16 15:00        NaN   122.0000        NaN        NaN 122.0000
## 17 16:00        NaN        NaN        NaN    256.000 256.0000
## 18 17:00     71.000   104.0000        242        NaN 139.0000
## 19 18:00     71.000        NaN        NaN        NaN  71.0000
## 20 19:00        NaN    79.0000        181    187.000 149.0000
## 21 20:00        NaN   232.0000         44     44.000 106.6667
## 22 21:00        NaN   161.0000        NaN        NaN 161.0000
## 23 22:00    178.000        NaN        107        NaN 142.5000
## 24 23:00        NaN        NaN        NaN        NaN      NaN
## 25  mean    162.375   155.6667        143    209.875 167.7292
#heatmap
#heatmaps
executeSavedPlot(data = allData, plotName = "meanBGheat_hist", libraryPath = libraryPath)

Sensor value by time and date with mean values

SGvalue_timeDaytable
##     time 2019-10-07 2019-10-08 2019-10-09 2019-10-10      mean
## 1  00:00  141.83333  102.16667  176.41667   99.00000 129.85417
## 2  01:00   95.33333   93.58333  132.16667  166.91667 122.00000
## 3  02:00  217.66667  186.25000  121.00000   93.08333 154.50000
## 4  03:00  301.66667  280.58333  141.91667  105.75000 207.47917
## 5  04:00  367.91667  331.16667   81.50000  216.50000 249.27083
## 6  05:00  400.00000  324.58333  106.41667  260.08333 272.77083
## 7  06:00  389.00000  301.41667  162.58333  323.50000 294.12500
## 8  07:00  338.25000  187.16667  225.50000  377.80000 282.17917
## 9  08:00  190.50000  106.41667  142.91667  234.90000 168.68333
## 10 09:00  169.41667  184.00000  123.33333  205.50000 170.56250
## 11 10:00  204.75000  189.08333   78.25000  190.50000 165.64583
## 12 11:00  197.00000  155.00000  103.16667   98.75000 138.47917
## 13 12:00        NaN  160.91667   77.58333   55.75000  98.08333
## 14 13:00  189.00000  162.33333   98.33333  213.75000 165.85417
## 15 14:00  188.08333  137.75000  299.00000  301.41667 231.56250
## 16 15:00  192.75000   96.58333  333.75000  260.83333 220.97917
## 17 16:00  174.08333  138.16667  269.00000  208.83333 197.52083
## 18 17:00  101.91667  100.66667  225.16667  111.91667 134.91667
## 19 18:00   92.50000   83.25000  209.91667   97.50000 120.79167
## 20 19:00   76.91667   88.58333  168.00000  162.33333 123.95833
## 21 20:00  130.08333  177.00000  138.58333   52.00000 124.41667
## 22 21:00   88.66667  154.75000  136.16667   94.33333 118.47917
## 23 22:00  120.08333  144.08333  106.33333  173.83333 136.08333
## 24 23:00  187.41667  135.08333  173.58333  122.58333 154.66667
## 25  mean  198.03623  167.52431  159.60764  176.14028 175.32711
#heatmap
#heatmaps
executeSavedPlot(data = allData, plotName = "meanSGheat_hist", libraryPath = libraryPath)

Interactive Plots

linePlots

barplots hourly

every 3 hours barplots

###daily barplots

boxplots hourly

3hour boxplots

daily boxplots